Databases are used to store information for an innumerable number of applications, including various commercial, industrial, technical, scientific and educational applications. Databases are generally organized into tables and fields and may be searched via database queries. A particular database may consist of many tables, and the tables in a database are generally related to each other.
A data warehouse is a repository of an enterprise's electronically stored data, designed to facilitate reporting and analysis. It is also a nonvolatile data repository that houses large amounts of historical data. Data warehousing and associated processing mechanisms, such as Online Analytical Processing (OLAP), Relational OLAP (ROLAP), Multidimensional OLAP (MOLAP), and Hybrid OLAP (HOLAP), are common technologies used to support business decisions and data analysis. One of the leading approaches used to store data in a data warehouse is the dimensional approach. In a dimensional approach, transaction data is partitioned into either “facts”, which are generally numeric transaction data such as net sales, quantity sold, gross sales, etc., or “dimensions”, which are the reference information that gives context to the facts.
The foundation of the enterprise data warehouse is a comprehensive and responsive logical data model. A logical data model is a representation of the way data is organized in a data warehouse environment. The logical data model specifically defines which individual data elements can be stored and how they relate to one another to provide a model of the business information. The data model ultimately defines which business questions can be answered from the data warehouse and thus determines the business value of the entire business decision support system.